Towards a high performance cellular automata programming skeleton

Autores
Printista, Alicia Marcela; Saez, Fernando
Año de publicación
2010
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Cellular automata provide an abstract model of parallel computation that can be effectively used for modeling and simulation of complex phenomena and systems. In this paper, we start from a skeleton designed to facilitate faster D-dimensional cellular automata application development. The key for the use of the skeleton is to achieve an efficient implementation, irrespective of the application specific details. In the parallel implementation on a cluster was important to consider issues such as task and data decomposition. With multicore clusters, new problems have emerged. The increasing numbers of cores per node, caches and shared memory inside the nodes, has led to the formation of a new hierarchy of access to processors. In this paper, we described some optimizations to restructuring the prototype code and exposing an abstracted view of the multicore cluster to the high performance CA application developer. The implementation of lattice division functions establishes a partnership relation among parallel processes. We propose that this relation can efficiently map on the multicore cluster communicational topology. We introduce a new mapping strategy that can obtain benefit in the performance by adapting its communication pattern to the hardware affinities among processes allocated in different cores. We apply our approach to a two-dimensional application achieving sensible execution time reduction.
Presentado en el X Workshop Procesamiento Distribuido y Paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
skeletal programming; multicore nodes; mapping strategy
Unbounded-action devices (e.g., cellular automata, circuits, networks of machines)
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/18924

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spelling Towards a high performance cellular automata programming skeletonPrintista, Alicia MarcelaSaez, FernandoCiencias Informáticasskeletal programming; multicore nodes; mapping strategyUnbounded-action devices (e.g., cellular automata, circuits, networks of machines)Cellular automata provide an abstract model of parallel computation that can be effectively used for modeling and simulation of complex phenomena and systems. In this paper, we start from a skeleton designed to facilitate faster D-dimensional cellular automata application development. The key for the use of the skeleton is to achieve an efficient implementation, irrespective of the application specific details. In the parallel implementation on a cluster was important to consider issues such as task and data decomposition. With multicore clusters, new problems have emerged. The increasing numbers of cores per node, caches and shared memory inside the nodes, has led to the formation of a new hierarchy of access to processors. In this paper, we described some optimizations to restructuring the prototype code and exposing an abstracted view of the multicore cluster to the high performance CA application developer. The implementation of lattice division functions establishes a partnership relation among parallel processes. We propose that this relation can efficiently map on the multicore cluster communicational topology. We introduce a new mapping strategy that can obtain benefit in the performance by adapting its communication pattern to the hardware affinities among processes allocated in different cores. We apply our approach to a two-dimensional application achieving sensible execution time reduction.Presentado en el X Workshop Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI)2010-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf220-228http://sedici.unlp.edu.ar/handle/10915/18924enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-9474-49-9info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:53:41Zoai:sedici.unlp.edu.ar:10915/18924Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:53:42.123SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Towards a high performance cellular automata programming skeleton
title Towards a high performance cellular automata programming skeleton
spellingShingle Towards a high performance cellular automata programming skeleton
Printista, Alicia Marcela
Ciencias Informáticas
skeletal programming; multicore nodes; mapping strategy
Unbounded-action devices (e.g., cellular automata, circuits, networks of machines)
title_short Towards a high performance cellular automata programming skeleton
title_full Towards a high performance cellular automata programming skeleton
title_fullStr Towards a high performance cellular automata programming skeleton
title_full_unstemmed Towards a high performance cellular automata programming skeleton
title_sort Towards a high performance cellular automata programming skeleton
dc.creator.none.fl_str_mv Printista, Alicia Marcela
Saez, Fernando
author Printista, Alicia Marcela
author_facet Printista, Alicia Marcela
Saez, Fernando
author_role author
author2 Saez, Fernando
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
skeletal programming; multicore nodes; mapping strategy
Unbounded-action devices (e.g., cellular automata, circuits, networks of machines)
topic Ciencias Informáticas
skeletal programming; multicore nodes; mapping strategy
Unbounded-action devices (e.g., cellular automata, circuits, networks of machines)
dc.description.none.fl_txt_mv Cellular automata provide an abstract model of parallel computation that can be effectively used for modeling and simulation of complex phenomena and systems. In this paper, we start from a skeleton designed to facilitate faster D-dimensional cellular automata application development. The key for the use of the skeleton is to achieve an efficient implementation, irrespective of the application specific details. In the parallel implementation on a cluster was important to consider issues such as task and data decomposition. With multicore clusters, new problems have emerged. The increasing numbers of cores per node, caches and shared memory inside the nodes, has led to the formation of a new hierarchy of access to processors. In this paper, we described some optimizations to restructuring the prototype code and exposing an abstracted view of the multicore cluster to the high performance CA application developer. The implementation of lattice division functions establishes a partnership relation among parallel processes. We propose that this relation can efficiently map on the multicore cluster communicational topology. We introduce a new mapping strategy that can obtain benefit in the performance by adapting its communication pattern to the hardware affinities among processes allocated in different cores. We apply our approach to a two-dimensional application achieving sensible execution time reduction.
Presentado en el X Workshop Procesamiento Distribuido y Paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
description Cellular automata provide an abstract model of parallel computation that can be effectively used for modeling and simulation of complex phenomena and systems. In this paper, we start from a skeleton designed to facilitate faster D-dimensional cellular automata application development. The key for the use of the skeleton is to achieve an efficient implementation, irrespective of the application specific details. In the parallel implementation on a cluster was important to consider issues such as task and data decomposition. With multicore clusters, new problems have emerged. The increasing numbers of cores per node, caches and shared memory inside the nodes, has led to the formation of a new hierarchy of access to processors. In this paper, we described some optimizations to restructuring the prototype code and exposing an abstracted view of the multicore cluster to the high performance CA application developer. The implementation of lattice division functions establishes a partnership relation among parallel processes. We propose that this relation can efficiently map on the multicore cluster communicational topology. We introduce a new mapping strategy that can obtain benefit in the performance by adapting its communication pattern to the hardware affinities among processes allocated in different cores. We apply our approach to a two-dimensional application achieving sensible execution time reduction.
publishDate 2010
dc.date.none.fl_str_mv 2010-10
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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